A comprehensive repository of semantic relations between verbs is of great importance in supporting a large area of natural language applications. The aim of this paper is to automatically generate a repository of semantic relations between verb pairs using Distributional Memory (DM), a state-of-the-art framework for distributional semantics. The main idea of our method is to exploit relationships that are expressed through prepositions between a verbal and a nominal event in text to extract semantically related events. Then using these prepositions, we derive relation types including causal, temporal, comparison, and expansion. The result of our study leads to the construction of a resource for semantic relations, which consists of pairs of verbs associated with their probable arguments and significance scores based on our measures. Experimental evaluations show promising results on the task of extracting and categorising semantic relations between verbs.
Publié le : 2019-04-26
Classification:  other areas of Computing and Informatics,  Semantically related verbs, temporal relations, cause-effect relations, related events knowledge base
@article{cai2019_1_240,
     author = {Hasan Zafari; Department of Computer Engineering, Malayer Branch, Islamic Azad University, Malayer and Maryam Hourali; Department of Information and Communication Technology (ICT), Malek-Ashtar University of Technology, Tehran},
     title = {From Parsed Corpora to Semantically Related Verbs},
     journal = {Computing and Informatics},
     volume = {37},
     number = {6},
     year = {2019},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai2019_1_240}
}
Hasan Zafari; Department of Computer Engineering, Malayer Branch, Islamic Azad University, Malayer; Maryam Hourali; Department of Information and Communication Technology (ICT), Malek-Ashtar University of Technology, Tehran. From Parsed Corpora to Semantically Related Verbs. Computing and Informatics, Tome 37 (2019) no. 6, . http://gdmltest.u-ga.fr/item/cai2019_1_240/